
On Sep 11, 2008, at 1:15 PM, Douglas Bates wrote:

>
> I should definitely add a check on p to the validate method.  (In some
> ways I'm surprised that it got as far as mer_finalize before kicking
> an error).  I suppose that p = 0 could be allowed and I could add some
> conditional code in the appropriate places but does it really make
> sense to have p = 0?  The random effects are defined to have mean
> zero.  If you have p = 0 that means that E[Y] = 0.  I would have
> difficulty imagining when I would want to make that restriction.
>
> Let me make this offer - if someone could suggest circumstances in
> which such a model would make sense, I will add the appropriate
> conditional code to allow for p = 0. For the time being I will just
> add a requirement of  p >  0 to the validate method.

I think it would make sense to consider a model in which E[Y] = 0 when  
the data are (either explicitly or implicitly) difference scores. (In  
fact, I tried to fit such a model with lmer a few months ago and ran  
into exactly this problem.)

- Pete


---
Peter Dixon
Department of Psychology
University of Alberta
Edmonton, Alberta, Canada
T6G 2E9
780-492-2318
780-492-1768 (fax)
peter.dixon@ualberta.ca



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